This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. This technological research and development project involves integration of several other technological projects, which are described in separate subproject forms. Glycomics is an emerging discipline, which still lags behind proteomics in terms of the development of bioinformatic tools that are required to track and process vast amounts of raw data, make it accessible to scientists with diverse backgrounds, and deduce important but non-obvious data relationships that can be interpreted in the context of developmental and pathological states of human cells. Our approach to this challenge is the development of an integrated data system that includes workflow protocols and tools for keeping track of experimental samples and processes, data processing tools to extract relevant information from the raw data, database schema to save the resulting data, and ontological tools that will facilitate access to the information and reveal systematic relationships within the data collected here, as well as among diverse data that is distributed in databases throughout the world and within the domain knowledge of the ontology itself. The basic design of this system has been developed, placing highest priority on the interoperability of its component parts. To this end we are developing three ontologies, GlycO, ReactO, and EnzyO, which incorporate knowledge of glycan structure, function, biosynthesis, and metabolism. These ontologies thus describe fundamental relationships between glycomics concepts and their association to experimental data, allowing individual elements of the data to be classified and viewed in the overall context of the biological/biochemical system. These ontologies will serve as the glue that ties the components of our bioinformatics system together and as a semantic basis for software applications that we will develop to facilitate data access and to reveal relationships within the data. A key component of our system is a graphical browsing and querying interface that we are developing. The highly integrated nature of our bioinformatics system for glycomics is a prerequisite for its optimal functionality, with each component being designed in a modular fashion that maintains consistency with the (implicit and explicit) knowledge contained in the ontologies.